KPI (Key Performance Indicator) anomaly detection method and system based on function type data analysis and medium

The invention provides a KPI (Key Performance Indicator) anomaly detection method and system based on function type data analysis and a medium. The method comprises the following steps of fitting discrete original KPI time sequence data into a dynamic function curve; extracting features of the dynamic function curve; inputting the extracted features of the dynamic function curve into a classification model, and performing anomaly identification on the features based on the classification model; and obtaining a recognition result about whether the original KPI time sequence data output by the classification model is abnormal or not. In order to solve the problems that the KPI anomaly detection method in the prior art is not high in detection precision and low in efficiency and cannot be applied to multi-scene or multi-dimensional anomaly detection, original KPI data are converted into a dynamic function curve, original data are converted into function type data for analysis, higher universality is achieved, an